非摘要分析
不同项目+数量趋势——plotly
# 导入 plotly 包
library(plotly)
# 输入数据
data <- data.frame(
Year = c(2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023),
`International(Regional)Cooperation Research and Exchange Projects` = c(0, 7, 0, 0, 0, 0, 0, 0),
`General Projects` = c(0, 0, 0, 1, 0, 2, 2, 4),
`Young Scientists Fund Projects` = c(1, 0, 1, 0, 1, 1, 4, 5),
`Regional Science Fund Projects` = c(0, 0, 0, 0, 0, 1, 1, 0)
)
# 将数据从宽格式转换为长格式
data_long <- tidyr::gather(data, key = "Project", value = "Number", -Year, na.rm = TRUE)
# 使用 gsub 替换 Project 列中的点号为空格
data_long$Project <- gsub("\\.", " ", data_long$Project)
# 创建颜色向量
color_vector <- c("#4E8FA0", "#8FC6B9", "#da735b", "#E7AC5F")
# 绘制 plotly 纵向折线图
plot <- plot_ly(data_long, x = ~Year, y = ~Number,
type = "scatter", # 折线图，以project为分；
mode = "lines+markers", # Any combination of "lines", "markers", "text" joined with a "+" OR "none".
# linetype = ~Project, # 根据项目设置线型
color = ~Project, # 设置颜色分类
colors = color_vector, # 设置颜色取值
width = 1200 , # 设置宽度
text = ~paste("Project: ", Project, "<br>Number: ", Number)) %>%
layout(title = 'Trends in NSFC-funded grants in implementation science by various projects',
xaxis = list(title = 'Year', type = 'category'), # 设置X轴为类别轴
yaxis = list(title = 'Number of grants'))
# 显示图形
plot
不同项目+数量趋势——ggplot2
# 使用 ggplot2 画图
plot <- ggplot(data_long, aes(x = Year, y = Number, linetype = Project)) +
geom_line(size = 1) +
labs(title = "Trends in NSFC-funded grants in implementation science by various projects",
x = "Year",
y = "Number of Projects") +
scale_color_manual(values = c("International (Regional) Cooperation Research and Exchange Projects" = "red",
"General Projects" = "blue",
"Young Scientists Fund Projects" = "green",
"Regional Science Fund Projects" = "purple")) + # 手动指定颜色
theme_minimal(base_size = 14) + # 设置基础字体大小
theme(legend.text = element_text(size = 10), legend.position = c(0.78, 0.85)) + # 调整图例字体大小
coord_cartesian(xlim = c(2016, 2024), ylim = c(0, 8))
# 显示图形
print(plot)
# 导出
jpeg("output/Trends_in_NSFC-funded_grants_in_IS_by_various_projects.jpeg", height = 2100, width = 4600, res = 300)
# 使用 ggplot2 画图
plot <- ggplot(data_long, aes(x = Year, y = Number, linetype = Project)) +
geom_line(size = 1) +
labs(title = "Trends in NSFC-funded grants in implementation science by various projects",
x = "Year",
y = "Number of Projects") +
scale_color_manual(values = c("International (Regional) Cooperation Research and Exchange Projects" = "red",
"General Projects" = "blue",
"Young Scientists Fund Projects" = "green",
"Regional Science Fund Projects" = "purple")) + # 手动指定颜色
theme_minimal(base_size = 14) + # 设置基础字体大小
theme(legend.text = element_text(size = 10), legend.position = c(0.78, 0.85)) + # 调整图例字体大小
coord_cartesian(xlim = c(2016, 2024), ylim = c(0, 8))
print(plot) # 需要print出来，才能保存到本地
dev.off()
## png
## 2
资助金额趋势——plotly（只有数量）
# 提供的数据
data <- data.frame(
"Chinese_yuan" = c("16.5", "17", "24", "28", "30", "33", "40", "41", "45", "48", "50", "500"),
"Number" = c(1, 1, 1, 1, 10, 1, 2, 3, 1, 2, 1, 15)
)
# 创建 Plotly 柱形图
plot <- plot_ly(data, x = ~Chinese_yuan, y = ~Number, type = 'bar',
marker = list(color = 'greyblue'),
text = ~Number, # ~paste("Number: ", Number)
hoverinfo = 'text', textposition = 'outside', textfont = list(color = 'black')) %>%
layout(
title = "Funding amount in NSFC-funded grants in implementation science",
xaxis = list(title = "Chinese Yuan"),
yaxis = list(title = "Number of Projects")
)
plot
资助金额趋势——plotly（分基金类别）
# 导入 plotly 包
library(plotly)
# 输入数据
data <- data.frame(
Project_Category = c(
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"Regional Science Fund Projects",
"Regional Science Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects"
),
Chinese_Yuan = c(
"500", "500", "500", "500", "500", "500", "500", "28", "33", "16.5", "17", "24", "30", "30", "30", "30", "30", "30", "30", "30", "30", "30", "40", "40", "41", "41", "41", "45", "48", "48", "50")
)
# 创建颜色向量
color_vector <- c("#4E8FA0", "#8FC6B9", "#da735b", "#E7AC5F")
# 创建柱状图
plot <- plot_ly(data, x = ~Chinese_Yuan, type = 'histogram',
color = ~Project_Category,
colors = color_vector,
width = 1200) %>%
layout(title = "Funding amount in NSFC-funded grants in IS",
xaxis = list(title = "Chinese Yuan"),
yaxis = list(title = "Number of Projects", tickangle = 0), # 旋转Y轴标签
legend = list(x = 1, y = 1), # 调整图例位置
bargap = 0.1) # 调整柱状图间隔，值越大间隔越宽
# 显示图形
plot
资助金额趋势——ggplot2
# 导入 ggplot2 包
library(ggplot2)
# 数据
data <- data.frame(
Project_Category = c(
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"International (Regional) Cooperation Research and Exchange Projects",
"Regional Science Fund Projects",
"Regional Science Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"Young Scientists Fund Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects",
"General Projects"
),
Chinese_Yuan = c(
"500", "500", "500", "500", "500", "500", "500", "28", "33", "16.5", "17", "24", "30", "30", "30", "30", "30", "30", "30", "30", "30", "30", "40", "40", "41", "41", "41", "45", "48", "48", "50")
)
# 创建颜色向量
colors <- c("#4E8FA0", "#8FC6B9", "#da735b", "#E7AC5F")
# 将 Chinese_Yuan 列转换为因子（factor）
data$Chinese_Yuan <- factor(data$Chinese_Yuan)
# 创建 ggplot2 柱形图
plot <- ggplot(data, aes(x = Chinese_Yuan, fill = Project_Category)) +
geom_bar(position = "dodge") + # 柱状图是独立的，不是嵌套在一起
scale_fill_manual(values = colors) + # 设置不同类别的填充颜色，使用指定的 colors 向量
labs(title = "Funding amount in NSFC-funded grants in IS", # 设置X、Y轴的图标
x = "Chinese Yuan",
y = "Number of Projects",
fill = "Project Category") +
theme_minimal() + # 最简洁主题，指的是底色是最简单的
geom_text(aes(label = ..count..), # 图表上增加文本，指的是图里的数字
stat = "count",
position = position_dodge(width = 1),
vjust = -0.5,
size = 4) +
scale_y_continuous(breaks = seq(0, max(table(data$Chinese_Yuan)), by = 2), # 设置Y轴的位置和现状
limits = c(0, max(table(data$Chinese_Yuan)) + 1)) +
theme(axis.text.x = element_text(angle = 45, hjust = 1), # 调整 x 轴文本的外观
plot.title = element_text(size = 20, hjust = 0.5)) # 调整图表标题的外观
# 显示图形
print(plot)
plotly_plot <- ggplotly(plot)
plotly_plot
# 导出
jpeg("output/Funding_amount_in_NSFC-funded_grants_in_IS.jpeg", height = 2100, width = 4600, res = 300)
# 创建 ggplot2 柱形图
plot <- ggplot(data, aes(x = Chinese_Yuan, fill = Project_Category)) +
geom_bar(position = "dodge") + # 柱状图是独立的，不是嵌套在一起
scale_fill_manual(values = colors) + # 设置不同类别的填充颜色，使用指定的 colors 向量
labs(title = "Funding amount in NSFC-funded grants in IS", # 设置X、Y轴的图标
x = "Chinese Yuan",
y = "Number of Projects",
fill = "Project Category") +
theme_minimal() + # 最简洁主题，指的是底色是最简单的
geom_text(aes(label = ..count..), # 图表上增加文本，指的是图里的数字
stat = "count",
position = position_dodge(width = 1),
vjust = -0.5,
size = 4) +
scale_y_continuous(breaks = seq(0, max(table(data$Chinese_Yuan)), by = 2), # 设置Y轴的位置和现状
limits = c(0, max(table(data$Chinese_Yuan)) + 1)) +
theme(axis.text.x = element_text(angle = 45, hjust = 1), # 调整 x 轴文本的外观
plot.title = element_text(size = 20, hjust = 0.5)) # 调整图表标题的外观
print(plot) # 需要print出来，才能保存到本地
dev.off()
## png
## 2
资助金额趋势——ggplot2
# 提供的数据
data <- data.frame(
"Chinese_yuan" = c("16.5", "17", "24", "28", "30", "33", "40", "41", "45", "48", "50", "500"),
"Number" = c(1, 1, 1, 1, 10, 1, 2, 3, 1, 2, 1, 7)
)
# 将 Chinese_yuan 列转换为字符型
data$Chinese_yuan <- as.character(data$Chinese_yuan)
# 指定颜色
colors <- c("#4E8FA0", "#8FC6B9", "#da735b", "#E7AC5F")
# 创建 ggplot2 柱形图
plot <- ggplot(data, aes(x = Chinese_yuan, y = Number)) +
geom_bar(stat = "identity", fill = "#808080") + # 使用灰黑色
labs(title = "Funding amount in NSFC-funded grants in implementation science",
x = "Chinese Yuan",
y = "Number of Projects") +
theme_minimal() +
theme(legend.position = "none", axis.text.x = element_text(angle = 45, hjust = 1),
plot.title = element_text(size = 20, hjust = 0.5)) + # 隐藏图例，旋转X轴标签
geom_text(aes(label = Number), vjust = -0.5, size = 7) + # 在每个柱子上方标注数值，调整字体大小
scale_y_continuous(breaks = seq(0, max(data$Number), by = 2), limits = c(0, max(data$Number) + 1)) # Y轴坐标刻度的步长和范围
print(plot)
# 导出
jpeg("output/Funding_amount_in_NSFC-funded_grants_in_IS.jpeg", height = 2100, width = 4600, res = 300)
# 创建 ggplot2 柱形图
plot <- ggplot(data, aes(x = Chinese_yuan, y = Number)) +
geom_bar(stat = "identity", fill = "#808080") + # 使用灰黑色
labs(title = "Funding amount in NSFC-funded grants in implementation science",
x = "Chinese Yuan",
y = "Number of Projects") +
theme_minimal() +
theme(legend.position = "none", axis.text.x = element_text(angle = 45, hjust = 1),
plot.title = element_text(size = 20, hjust = 0.5)) + # 隐藏图例，旋转X轴标签
geom_text(aes(label = Number), vjust = -0.5, size = 7) + # 在每个柱子上方标注数值，调整字体大小
scale_y_continuous(breaks = seq(0, max(data$Number), by = 2), limits = c(0, max(data$Number) + 1)) # Y轴坐标刻度的步长和范围
print(plot) # 需要print出来，才能保存到本地
dev.off()
## png
## 2
学部
library(DT) # DT 包提供了用于创建交互式、可排序和可过滤数据表格的功能。它可以用于在 Shiny 应用程序中嵌入，从而创建具有交互性的Web应用。
library(formattable) # formattable 包用于美化数据表，使其更易读和更具吸引力。它提供了各种格式化选项，允许你更改单元格的颜色、添加注释、设置小数位数等
# 提供的数据
data <- data.frame(
"Project Category" = c("International (Regional) Cooperation Research and Exchange Projects",
"Young Scientists Fund Projects", "General Projects", "Regional Science Fund Projects"),
"Number" = c(15, 13, 9, 2)
)
# 使用 formattable 包进行格式化
formatted_data <- formattable::formattable(data, list(
`计数` = color_tile("white", "orange")
))
# 使用 DT 包创建数据表
datatable(formatted_data, options = list(searching = TRUE), rownames = FALSE)
学科
# 提供的数据
data <- data.frame(
"Science Department" = c("Macro Management and Policy (G04)", "Preventive Medicine (H30)", "Mental Health and Psychology (H10)", "Oncology (H18)"),
"Number" = c(22, 15, 1, 1),
"Proportion" = c("56.4%", "38.5%", "2.6%", "2.6%")
)
# # 使用 formattable 包进行格式化——能给单元格背景增加颜色
# formatted_data <- formattable::formattable(data, list(
# `Number` = color_tile("white", "orange"),
# `Proportion` = color_tile("white", "orange")
# ))
# 使用 DT 包创建数据表——能做成交互表格（适合数据量多的）
## 去掉行号，并设置 "Number" 列名和 "Number" 和 "Proportion" 列的数据左对齐
datatable(data, options = list(searching = TRUE), rownames = FALSE,
caption = htmltools::tags$caption( # 使用htmltools包中的tags函数来创建HTML标签
style = 'caption-side: bottom; text-align: center;', # 文字放置在底部，居中
'Table 2: ', # 文本
htmltools::em('This is a simple caption for the table.') # 创建一个HTML <em> 标签，将其中的文本 "This is a simple caption for the table." 显示为强调样式（通常是斜体）
)
)
# # autoHideNavigation = TRUE) %>%
# formatStyle(
# columns = c("Number", "Proportion"),
# textAlign = 'left'
# )
# list(dom = 't'), 不用加上去
# editable = TRUE，使得表格可编辑
# filter = "top"，是一个筛选功能
# 在R中，使用DT包创建表格时，可以通过 caption 参数来指定表格标题。这个参数的值可以是一个字符串，也可以是一个包含HTML标签的字符串。如果你想要更灵活地定义标题的样式或添加其他HTML元素，可以使用htmltools包中的tags函数来创建HTML标签。
# 在上述代码中，使用了htmltools::tags$caption(...)来创建 <caption> 标签，并在其中定义了样式（style）和文本内容。这样可以定制化标题的外观和样式，而不仅仅是简单的纯文本标题。
# callback 参数允许你指定一个 JavaScript 回调函数，用于自定义表格的行为。JavaScript 回调函数是在客户端（浏览器）中执行的代码片段，可以用于处理用户与表格的交互、响应事件等。通过 callback 参数，你可以传递自定义的 JavaScript代码，以便在特定的表格事件发生时执行一些自定义的操作。例如，你可以使用回调函数来处理表格的点击、排序、过滤等事件。一个简单的示例是在表格中的某一列被点击时，弹出一个警告框。